Efficient Attribute (α,β)-Core Detection in Large Bipartite Graphs (Student Abstract)

Authors

  • Yanping Wu Zhejiang Gongshang University
  • Renjie Sun Zhejiang Gongshang University
  • Chen Chen Zhejiang Gongshang University
  • Xiaoyang Wang Zhejiang Gongshang University

DOI:

https://doi.org/10.1609/aaai.v36i11.21680

Keywords:

Attribute Bipartite Graphs, Community Detection, Cohesive Subgraph

Abstract

In this paper, we propose a novel problem, named rational (alpha, beta)-core detection in attribute bipartite graphs (RCD-ABG), which retrieves the connected (alpha, beta)-core with the largest rational score. A basic greedy framework with an optimized strategy is developed and extensive experiments are conducted to evaluate the performance of the techniques.
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Published

2022-06-28

How to Cite

Wu, Y., Sun, R., Chen, C., & Wang, X. (2022). Efficient Attribute (α,β)-Core Detection in Large Bipartite Graphs (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13087-13088. https://doi.org/10.1609/aaai.v36i11.21680

Issue

Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Section

AAAI Student Abstract and Poster Program